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WeatherGFM: Learning A Weather Generalist Foundation Model via In-context Learning
Xiangyu Zhao, Zhiwang Zhou, Wenlong Zhang +9
The Earth's weather system encompasses intricate weather data modalities and diverse weather understanding tasks, which hold significant value to human life. Existing data-driven m…
DiffSR: Learning Radar Reflectivity Synthesis via Diffusion Model from Satellite Observations
Xuming He, Zhiwang Zhou, Wenlong Zhang +4
Weather radar data synthesis can fill in data for areas where ground observations are missing. Existing methods often employ reconstruction-based approaches with MSE loss to recons…
MambaDS: Near-Surface Meteorological Field Downscaling with Topography Constrained Selective State Space Modeling
Zili Liu, Hao Chen, Lei Bai +4
In an era of frequent extreme weather and global warming, obtaining precise, fine-grained near-surface weather forecasts is increasingly essential for human activities. Downscaling…
Fast Information Streaming Handler (FisH): A Unified Seismic Neural Network for Single Station Real-Time Earthquake Early Warning
Tianning Zhang, Feng Liu, Yuming Yuan +3
Existing EEW approaches often treat phase picking, location estimation, and magnitude estimation as separate tasks, lacking a unified framework. Additionally, most deep learning mo…
VegeDiff: Latent Diffusion Model for Geospatial Vegetation Forecasting
Sijie Zhao, Hao Chen, Xueliang Zhang +3
In the context of global climate change and frequent extreme weather events, forecasting future geospatial vegetation states under these conditions is of significant importance. Th…